This column is written for those interested in learning about the world of Data for Good, where statistical analysis is dedicated to good causes that benefit our lives, our communities, and our world. If you would like to know more or have ideas for articles, contact David Corliss.

David Corliss is the principal data scientist at Grafham Analytics and the founder of Peace-Work, a Data for Good nongovernmental organization.

This has been an amazing year in Data for Good, with outstanding accomplishments in many areas. Statisticians and data scientists across the analytic spectrum have taken on the most important challenges facing us and our world. The importance of analytics in addressing these concerns cannot be overstated, and the growing D4G community rises to meet them in an ever-increasing number of ways.

This year will be remembered as the year large language models came of age, putting ethical use of artificial intelligence at center stage. Ethical best practices in statistics, machine learning, and AI have long been of concern to the analytic community, and the ASA has played a leading role in establishing best practices. In the past year, as large language models have gone mainstream, the public has become more aware of the need for a solid ethical foundation for statistical practice. In response, new ethical AI groups have sprung up all around.

As Data for Good leaders, we need to be foremost in raising concerns about use, data security, and fairness and finding answers to these concerns. With this larger, more public role, Data for Good has become more than analytic projects serving humanity and, as ethical scientists, we share a commitment to serving the public on matters of ethical practice—informing, advocating, and guiding the development of statistical science as a pillar of modern society for the benefit of all.

We also saw tremendous accomplishment and growth for the ASA Justice, Equity, Diversity, and Inclusion (JEDI) Outreach Group. Since its launch, JEDI has bloomed into a Data for Good powerhouse! JEDI Corner has become the place for JEDIs to keep up to date on events, research, and opportunities. JEDI-sponsored sessions at JSM expand every year, each inspiring further research, opening up new areas and applications, and welcoming a wider audience. Plans are in the works for even more in 2024, so be sure to read JEDI Corner to keep up with new opportunities in Data for Good.

In January, Stats4Good highlighted a group of issues as top priorities for the D4G community in 2023. It is now my great pleasure to recognize outstanding accomplishments this year in each of the five areas:

• Biostatistics Challenge: Leveraging COVID Learnings. The recognition honors Bhramar Mukherjee and her team at the University of Michigan, whose modeling of the development of COVID in India will help track and forecast future epidemics. Mukherjee was honored with the ASA’s Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society for this work.
• Environmental Advocacy: Climate Change Impacts and Remediation. This recognition is given to the NASA Data Resources for Climate Change website, a treasure trove of data supporting an endless list of use cases in the analysis of climate change. For statisticians and data scientists in environmental advocacy—or someone new, such as a student looking for a first project in D4G—this website is a must on your bookmark list.
• The 2023 Data for Good Challenge in Data. The 2023 challenge honor for data research goes to Felipe Aros-Vera from Ohio University for his work on human trafficking using multiple system estimation.
• Data for Good Organization and Infrastructure. This recognition goes to Eric Vance for leading the Laboratory for Interdisciplinary Statistical Analysis program at the University of Colorado. The program has long been a leader for developing collaborations with nonstatisticians, empowering statisticians and data scientists to take a leading role in projects driving better outcomes for society with statistics.
• Human Rights. This year’s recognition goes to Stephanie Cook of New York University for her outstanding work as a statistician with NYU’s Critical Race Digital Studies program.